Mohammad Farhan Al. Qudah

The current study aims to identify the level and proportions of smartphone addiction, and academic procrastination among university students in the light of the Corona pandemic; identify the differences in smartphone addiction, academic procrastination, and quality of life according to gender and stage of study; and revealing the predictive ability of academic procrastination and quality of life for smartphone addiction. Methods: 556 male and female students from Saudi universities participated in the study, whose ages ranged from 18 to 52 years. Measures of academic procrastination and quality of life were used, in addition to the Italian scale of smartphone addiction, which was translated and checked for validity and reliability. Results: The results revealed that 37.4% of the sample were addicted to smartphone use, while 7.7% had a high level of procrastination, and 62.8% had an average level of procrastination. The results did not show statistically significant differences in smartphone addiction and quality of life according to gender and educational stage, while there were statistically significant differences in academic procrastination according to gender in favor of males, and according to stage of education in favor of undergraduate students. The results also revealed a statistically significant positive relationship between academic procrastination and smartphone addiction, and a statistically significant negative relationship between smartphone addiction and quality of life. A negative relationship between quality of life and academic procrastination was found. The results also revealed that addiction to smartphones could be predicted through academic procrastination and quality of life.

This study explores the level and frequency of anxiety about COVID-19 infection in some Middle Eastern countries, and differences in this anxiety by country, gender, workplace, and social status. Another aim was to identify the predictive power of anxiety about COVID-19 infection, daily smartphone use hours, and age in smartphone addiction. The participants were 651 males and females from Jordan, Saudi Arabia, the United Arab Emirates, and Egypt. The participants’ ages ranged between 18 and 73 years (M 33.36, SD = 10.69). A questionnaire developed by the authors was used to examine anxiety about COVID-19 infection. Furthermore, the Italian Smartphone Addiction Inventory was used after being translated, adapted, and validated for the purposes of the present study. The results revealed that the percentages of participants with high, average, and low anxiety about COVID-19 infection were 10.3%, 37.3%, and 52.4%, respectively. The mean scores of anxiety about COVID-19 infection in the four countries were average: Egypt (M = 2.655), Saudi Arabia (M = 2.458), the United Arab Emirates (M = 2.413), and Jordan (M = 2.336). Significant differences in anxiety about COVID-19 infection were found between Egypt and Jordan, in favor of Egypt. Significant gender differences were found in favor of females in the Jordanian and Egyptian samples, and in favor of males in the Emirati sample. No significant differences were found regarding workplace and social status. The results also revealed a significant positive relationship between anxiety about COVID-19 infection, daily smartphone use hours, and age on the one hand, and smartphone addiction on the other. The strongest predictor of smartphone addiction was anxiety about COVID-19 infection, followed by daily use hours. Age did not significantly contribute to the prediction of smartphone addiction. The study findings shed light on the psychological health and cognitive aspects of anxiety about COVID-19 infection and its relation to smartphone addiction.

The present study aimed to explore the relationship between cyber-bullying and psychological security, psychological loneliness, and age. In other words, it sought to identify the predictive power of these three variables on cyber-bullying among university students. Participants were 426 male and female Saudi university students aged between 18 and 36 years (M = 21.00, SD = 2.42). Three scales were used to probe cyber-bullying and psychological security and loneliness. Data analysis revealed that 17.6% of the participants were cyber-bullies. Significant differences in cyber-bullying were found by gender (in favor of males). A significant positive correlation was found between cyber-bullying on one hand and psychological security and loneliness and age on the other. The findings also revealed that cyber-bullying among university students can be predicted by psychological loneliness and age. Psychological loneliness is the best predictor of cyber-bullying. It explained .284 of cyber-bullying, while age, psychological loneliness explained .339 of cyber-bullying. These findings shed more light on the psychological aspects included in cyber-bullying. It is a significant contribution in that it identified the motives beyond cyber-bullying and its adverse effects on individuals.